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Record W1768032604 · doi:10.1017/s0954579415000036

Using cross-species comparisons and a neurobiological framework to understand early social deprivation effects on behavioral development

2015· review· en· W1768032604 on OpenAlexaff
Zoë H. Brett, Kathryn L. Humphreys, Alison S. Fleming, Gary W. Kraemer, Stacy S. Drury

Bibliographic record

VenueDevelopment and Psychopathology · 2015
Typereview
Languageen
FieldPsychology
TopicNeuroendocrine regulation and behavior
Canadian institutionsUniversity of Toronto
FundersNational Institute of Mental Health
KeywordsPsychologyMaternal deprivationDevelopmental psychologySocial deprivationImpulsivityNeuroscienceCognitive psychology

Abstract

fetched live from OpenAlex

Building upon the transactional model of brain development, we explore the impact of early maternal deprivation on neural development and plasticity in three neural systems: hyperactivity/impulsivity, executive function, and hypothalamic-pituitary-adrenal axis functioning across rodent, nonhuman primate, and human studies. Recognizing the complexity of early maternal-infant interactions, we limit our cross-species comparisons to data from rodent models of artificial rearing, nonhuman primate studies of peer rearing, and the relations between these two experimental approaches and human studies of children exposed to the early severe psychosocial deprivation associated with institutional care. In addition to discussing the strengths and limitations of these paradigms, we present the current state of research on the neurobiological impact of early maternal deprivation and the evidence of sensitive periods, noting methodological challenges. Integrating data across preclinical animal models and human studies, we speculate about the underlying biological mechanisms; the differential impact of deprivation due to temporal factors including onset, offset, and duration of the exposure; and the possibility and consequences of reopening of sensitive periods during adolescence.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.384
GPT teacher head0.494
Teacher spread0.109 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations43
Published2015
Admission routes1
Has abstractyes

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